• 드라이브 ㆍ 컨트롤
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• 제20권4호
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• pp.71-79
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• 2023

In the field of agricultural machinery, various on-field tests are conducted to measure design load for optimal design of agricultural equipment. However, field test procedures are costly and time-consuming, and there are many constraints on field soil conditions due to weather, so research on utilizing simulation to overcome these shortcomings is needed. Therefore, this study aimed to model agricultural soils using discrete element method (DEM) software. To simulate draft force, predictions are made according to travel speed and compared to field test results to validate the prediction accuracy. The measured soil properties are used for DEM modeling. In this study, the soil property measurement procedure was designed to measure the physical and mechanical properties. DEM soil model calibration was performed using a virtual vane shear test instead of the repose angle test. The DEM simulation results showed that the prediction accuracy of the draft force was within 4.8% (2.16~6.71%) when compared to the draft force measured by the field test. In addition, it was confirmed that the result was up to 72.51% more accurate than those obtained through theoretical methods for predicting draft force. This study provides useful information for the DEM soil modeling process that considers the working speed from the perspective of agricultural machinery research and it is expected to be utilized in agricultural machinery design research.

• 드라이브 ㆍ 컨트롤
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• 제20권4호
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• pp.27-34
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• 2023

Weeding in orchards is closely associated with productivity and quality. The customary weeding process is both labor-intensive and time-consuming. To solve the problems, there is need for automation of agricultural robots and machines in the agricultural field. On the other hand, orchards have complicated working areas due to narrow spaces between trees and amorphous terrain. Therefore, it is necessary to develop customized robot technology for unmanned weeding work within the department. This study developed a path generation and path control method for unmanned weeding according to the orchard environment. For this, the width of the weeding span, the number of operations, and the width of the weeding robot were used as input parameters for the orchard environment parameters. To generate a weeding path, a weeding robot was operated remotely to obtain GNSS-based location data along the superheated center line, and a driving performance test was performed based on the generated path. From the results of orchard field tests, the RMSE in weeding period sections was measured at 0.029 m, with a maximum error of 0.15 m. In the steering period within row and steering to the next row sections, the RMSE was 0.124 m, and 0.047 m, respectively.

• 드라이브 ㆍ 컨트롤
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• 제20권4호
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• pp.1-8
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• 2023

In recent years, robots have been utilized in various industries to reduce workload and enhance work efficiency. The following mobility offers users convenience by autonomously tracking specific locations and targets without the need for additional equipment such as forklifts or carts. In this paper, deep learning techniques were employed to recognize individuals and assign each of them a unique identifier to enable the recognition of a specific person even among multiple individuals. To achieve this, the distance and angle between the robot and the targeted individual are transmitted to respective controllers. Furthermore, this study explored the control methodology for mobility that tracks a specific person, utilizing Simultaneous Localization and Mapping (SLAM) and Proportional-Integral-Derivative (PID) control techniques. In the PID control method, a genetic algorithm is employed to extract the optimal gain value, subsequently evaluating PID performance through simulation. The SLAM method involves generating a map by synchronizing data from a 2D LiDAR and a depth camera using Real-Time Appearance-Based Mapping (RTAB-MAP). Experiments are conducted to compare and analyze the performance of the two control methods, visualizing the paths of both the human and the following mobility.

• 드라이브 ㆍ 컨트롤
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• 제21권1호
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• pp.38-45
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• 2024

The power delivery is crucial to designing agricultural machinery. Therefore, the tractor-mounted potato harvester was used in this study to conduct the field experiment and analyze the power delivery for each step. This study was focused on an analysis of power delivery from the engine to the hydraulic components for the tractor-mounted harvester during potato harvesting. Finally, the simulation model of a self-propelled potato harvester was developed and validated using the experimental dataset of the tractor-mounted potato harvester. The power delivery analysis showed that approximately 90.22% of the engine power was used as traction power to drive the tractor-mounted harvester, and only 5.10% of the engine power was used for the entire hydraulic system of the tractor and operated the harvester. The statistical analysis of the simulation and experimental results showed that the coefficient of determinations (R²) ranged from 0.80 to 0.96, which indicates that the simulation model was performed with an accuracy of over 80%. The regression models were correlated linearly with the simulation and experimental results. Therefore, we believe that this study could contribute to the design methodology and performance test procedure of agricultural machinery. This basic study would be helpful in the design of a self-propelled potato harvester.

• 드라이브 ㆍ 컨트롤
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• 제21권1호
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• pp.22-30
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• 2024

Gearboxes designed for reciprocating motion operating mechanisms operate under conditions where both the load and speed undergo continuous variations. When conducting durability tests on gearboxes designed for such applications, operating the target gearbox under conditions similar to the intended usage is essential. The gearbox must be operated for the required number of cycles to validate its durability under conditions mirroring its intended usage. This study devised an accelerated test method for gearboxes, which reduces operating angles and operational strokes. The reliability of the accelerated test was verified by comparing the stresses imposed on the gears under general and acceleration conditions through multi-body dynamic simulations. The results confirmed that the maximum contact stress levels under normal and accelerated conditions were within a 0.1% error range, indicating a minimal difference in the gear damage rates. However, a difference in the maximum contact stress results between the normal and accelerated conditions was observed when inertial forces acted on the output shaft due to the operational acceleration of the gearbox. Therefore, when conducting this acceleration test, caution should be exercised to ensure that the operational load on the gearbox, which affects inertia, does not significantly deviate from the conditions observed under normal operating conditions.

• 드라이브 ㆍ 컨트롤
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• 제21권2호
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• pp.23-29
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• 2024

Potatoes are one of the world's four major crops, and domestic consumption is currently increasing in Korea. However, the mechanization rate of potatoes is very low, and especially, harvesting is the most labor-intensive task in potato production. In Korea, potato-collecting work depends on manpower, so it is necessary to develop a gathering-type harvester that can be used for processes from digging to harvesting. Therefore, in this study, a self-propelled-type potato harvester was developed, and its performance was analyzed to mechanize harvesting. The potato harvester was developed to have a crawler-type driving part with a 60 hp diesel engine and consisted of a digging part that digs potatoes from the ground, a vertical transporting part that transfers the dug potatoes to the height of the collection bag, a separating part that separates debris, such as stones and soil, and a collecting part that loads the collection box. A field test of the potato harvester was conducted, and performance was evaluated by the damage, loss, and debris mixing proportions, which were 2.5%, 2.8%, and 2.6%, respectively. The working capacity was 1.2 h/10 a. The economic analysis results showed that the cost of harvesting work could be reduced by 12.7% compared to manual harvesting.

• 드라이브 ㆍ 컨트롤
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• 제21권2호
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• pp.30-35
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• 2024

Domestic rice is more expensive than imported products, so it is necessary to reduce production costs to secure competitiveness. Low-density planting developed in Japan is a cultivation technology that reduces labor and production costs without yield loss. The area of low-density cultivation is continuously increasing. However, research on how rice transplanters adapt to low-density planting has not been conducted. Therefore, this study was carried out to determine the optimal working conditions of a rice transplanter for low-density planting. Three types of rice transplanters were used and treated based on 3 conveying distance levels. The number of picked seedlings, pick missing rate, the number of planted seedlings, and the mis-planted rate were investigated to evaluate planting accuracy according to the transfer distance to the seedling tray. The results showed that the number of planted seedlings was 4.31~4.95 EA with an L1 seedling tray transfer distance (horizontal 9 mm, vertical 8 mm), but the mis-planted rate was higher than in other conditions. At L2 (horizontal 9 mm, vertical 10 mm) and L3 (horizontal 11 mm, vertical 8 mm) transfer distance conditions, the number of planted seedlings were 4.89-5.68 EA and 4.69-5.66 EA, respectively, with a low mis-planted rate of less than 3%. The results showed that if the transfer distance is adjusted properly, a rice transplanter can be used for low-density planting with high planting accuracy.

• 드라이브 ㆍ 컨트롤
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• 제21권2호
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• pp.36-43
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• 2024

The yield is basic and necessary information in precision agriculture that reduces input resources and enhances productivity. Yield information is important because it can be used to set up farming plans and evaluate farming results. Yield monitoring systems are commercialized in the United States and Japan but not in Korea. Therefore, such a system must be developed. This study was conducted to develop a yield monitoring system that improved performance by correcting a previously developed flow sensor using a grain tank-weighing system. An impact-plated type flow sensor was installed in a grain tank where grains are placed, and grain tank-weighing sensors were installed under the grain tank to estimate the weight of the grain inside the tank. The grain flow rate and grain weight prediction models showed high correlations, with coefficient of determinations (R2) of 0.9979 and 0.9991, respectively. A main controller of the yield monitoring system that calculated the real-time yield using a sensor output value was also developed and installed in a combine harvester. Field tests of the combine harvester yield monitoring system were conducted in a rice paddy field. The developed yield monitoring system showed high accuracy with an error of 0.13%. Therefore, the newly developed yield monitoring system can be used to predict grain weight with high accuracy.

• 드라이브 ㆍ 컨트롤
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• 제21권2호
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• pp.44-52
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• 2024

In this study, we predicted PTO power requirements based on torque predicted by the discrete element method and the multi-body dynamics coupling method. Six different scenarios were simulated to predict PTO power requirements in different soil conditions. The first scenario was a tillage operation on cohesionless soil, and the field was modeled using the Hertz-Mindlin contact model. In the second through sixth scenarios, tillage operations were performed on viscous soils, and the field was represented by the Hertz-Mindlin + JKR model for cohesion. To check the influence of surface energy, a parameter to reproduce cohesion, on the power requirement, a simple regression analysis was performed. The significance and appropriateness of the regression model were checked and found to be acceptable. The study findings are expected to be used in design optimization studies of agricultural machinery by predicting power requirements using the discrete element method and the multi-body dynamics coupling method and analyzing the effect of soil cohesion on the power requirement.

• 드라이브 ㆍ 컨트롤
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• 제21권2호
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• pp.53-64
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• 2024

Global population growth has resulted in an increased demand for food production. Simultaneously, aging rural communities have led to a decrease in the workforce, thereby increasing the demand for automation in agriculture. Drones are particularly useful for unmanned pest control fields. However, the current method of uniform spraying leads to environmental damage due to overuse of pesticides and drift by wind. To address this issue, it is necessary to enhance spraying performance through precise performance evaluation. Therefore, as a foundational study aimed at optimizing drone-based pest control technologies, this research evaluated water-sensitive paper (WSP) via density map estimation using convolutional neural networks (CNN) with a encoder-decoder structure. To achieve more accurate estimation, this study implemented multi-task learning, incorporating an additional classifier for image segmentation alongside the density map estimation classifier. The proposed model in this study resulted in a R-squared (R²) of 0.976 for coverage area in the evaluation data set, demonstrating satisfactory performance in evaluating WSP at various density levels. Further research is needed to improve the accuracy of spray result estimations and develop a real-time assessment technology in the field.